A database of global wetland validation samples （GWVS） is the foundation for wetland mapping on a global scale. In this work, a database of GWVS was created based on 25 “wetland-related” keyw ord searches of a tot...A database of global wetland validation samples （GWVS） is the foundation for wetland mapping on a global scale. In this work, a database of GWVS was created based on 25 “wetland-related” keyw ord searches of a total of 3,506 full-text documents downloaded from the Web of Science. Eight hundred and three samples from a total of 68 countries and 14i protected areas were recorded by the GWVS, including samples of marine/coastal wetlands, inland wet- lands and human-made wetlands, at ratios of 53 %, 41% and 6 %, respectively. The results exhibit spatial distribution among Terrestrial Ecoregions of the World, the World Database on Protected Areas and the Database of Global Administrative Areas. Within most of the biomes, protected areas and countries examined, the very low concentration of samples requires more attention in the future. The greatest concentration of samples within a single biome is found in the tropical and subtropical moist broadleaf forest biome, accounting for 27 % of the total samples, while no sample is found in the biome of tropical and subtropical coniferous woodland. Greater efforts are expected to be made to record samples in Oceania, Central Europe, Northern Europe, Northern Africa, Central Africa, Central America, the Caribbean, and midwestern South America. Our data show that it is feasible to map global wetlands using Landsat TM/ ETM＋ at 30-m resolution. The continued improvement of the GWVS sharing platform should be reinforced in the future, making a strong contribution to global wetland mapping and monitoring.展开更多
This paper uses an urbanized high-resolution land data assimilation system(u-HRLDAS) to parameterize the urban land surface characteristics.The u-HRLDAS model is localized and developed in order to satisfy the need of...This paper uses an urbanized high-resolution land data assimilation system(u-HRLDAS) to parameterize the urban land surface characteristics.The u-HRLDAS model is localized and developed in order to satisfy the need of the weather forecast in Beijing,China.The remote sensing data used to localize and drive u-HRLDAS include the soil type data and MODIS retrieved leaf area index(LAI) data.The evaporation and water depth for impervious surface in urban area are developed to improve the simulation of u-HRLDAS.The result of the urban weather forecast is used for the comparison based on the rapid update cycle system at Beijing Meteorological Bureau(BJ-RUC) without coupled with u-HRLDAS.The land surface temperature,land surface fluxes,and first layer soil moisture in several single sites and urban Beijing region by BJ-RUC are compared with u-HRLDAS after localization and development.The off-line simulation results indicate that compared with BJ-RUC,after the localization and development,u-HRLDAS can improve the simulation of land surface parameters and fluxes definitely.展开更多
基金Supported by the National Basic Research Program of China under Grant No.2007CB807902the National High-Tech Research and Development Plan of China under Grant No.2006AA01Z423~~
基金supported by the National Science and Technology Support Program(2012BAJ24B01)the National Natural Science Foundation of China(41201445+1 种基金41271423)the National High Technology Research and Development Program of China(2009AA122003)
文摘A database of global wetland validation samples （GWVS） is the foundation for wetland mapping on a global scale. In this work, a database of GWVS was created based on 25 “wetland-related” keyw ord searches of a total of 3,506 full-text documents downloaded from the Web of Science. Eight hundred and three samples from a total of 68 countries and 14i protected areas were recorded by the GWVS, including samples of marine/coastal wetlands, inland wet- lands and human-made wetlands, at ratios of 53 %, 41% and 6 %, respectively. The results exhibit spatial distribution among Terrestrial Ecoregions of the World, the World Database on Protected Areas and the Database of Global Administrative Areas. Within most of the biomes, protected areas and countries examined, the very low concentration of samples requires more attention in the future. The greatest concentration of samples within a single biome is found in the tropical and subtropical moist broadleaf forest biome, accounting for 27 % of the total samples, while no sample is found in the biome of tropical and subtropical coniferous woodland. Greater efforts are expected to be made to record samples in Oceania, Central Europe, Northern Europe, Northern Africa, Central Africa, Central America, the Caribbean, and midwestern South America. Our data show that it is feasible to map global wetlands using Landsat TM/ ETM＋ at 30-m resolution. The continued improvement of the GWVS sharing platform should be reinforced in the future, making a strong contribution to global wetland mapping and monitoring.
基金supported by National Natural Science Foundation of China(Grant No. 41005056)Key Projects in the National Science & Technology Pillar Program during the Eleventh Five-Year Plan Period (GrantNo. 2008BAC37B04)
文摘This paper uses an urbanized high-resolution land data assimilation system(u-HRLDAS) to parameterize the urban land surface characteristics.The u-HRLDAS model is localized and developed in order to satisfy the need of the weather forecast in Beijing,China.The remote sensing data used to localize and drive u-HRLDAS include the soil type data and MODIS retrieved leaf area index(LAI) data.The evaporation and water depth for impervious surface in urban area are developed to improve the simulation of u-HRLDAS.The result of the urban weather forecast is used for the comparison based on the rapid update cycle system at Beijing Meteorological Bureau(BJ-RUC) without coupled with u-HRLDAS.The land surface temperature,land surface fluxes,and first layer soil moisture in several single sites and urban Beijing region by BJ-RUC are compared with u-HRLDAS after localization and development.The off-line simulation results indicate that compared with BJ-RUC,after the localization and development,u-HRLDAS can improve the simulation of land surface parameters and fluxes definitely.
